model.rb in ruby-dnn-0.7.2

- old
+ new

@@ -149,19 +149,21 @@
         epoch_proc.call(epoch) if epoch_proc
       end
     end
   
     def train_on_batch(x, y, &batch_proc)
+      input_data_shape_check(x, y)
       x, y = batch_proc.call(x, y) if batch_proc
       forward(x, true)
       loss_value = loss(y)
       backward(y)
       update
       loss_value
     end
   
     def accurate(x, y, batch_size = 1, &batch_proc)
+      input_data_shape_check(x, y)
       batch_size = batch_size >= x.shape[0] ? x.shape[0] : batch_size
       correct = 0
       (x.shape[0].to_f / batch_size).ceil.times do |i|
         x_batch = Xumo::SFloat.zeros(batch_size, *x.shape[1..-1])
         y_batch = Xumo::SFloat.zeros(batch_size, *y.shape[1..-1])
@@ -183,10 +185,11 @@
       end
       correct.to_f / x.shape[0]
     end
   
     def predict(x)
+      input_data_shape_check(x)
       forward(x, false)
     end
 
     def predict1(x)
       predict(Xumo::SFloat.cast([x]))[0, false]
@@ -237,11 +240,15 @@
     end
 
     def get_prev_layer(layer)
       layer_index = @layers.index(layer)
       prev_layer = if layer_index == 0
-        @super_model.layers[@super_model.layers.index(self) - 1]
+        if @super_model
+          @super_model.layers[@super_model.layers.index(self) - 1]
+        else
+          self
+        end
       else
         @layers[layer_index - 1]
       end
       if prev_layer.is_a?(Layers::Layer)
         prev_layer
@@ -259,20 +266,33 @@
       unless @layers.last.is_a?(Layers::OutputLayer)
         raise TypeError.new("The last layer is not an OutputLayer.")
       end
     end
 
+    def input_data_shape_check(x, y = nil)
+      unless @layers.first.shape == x.shape[1..-1]
+        raise DNN_ShapeError.new("The shape of x does not match the input shape. x shape is #{x.shape[1..-1]}, but input shape is #{@layers.first.shape}.")
+      end
+      if y && @layers.last.shape != y.shape[1..-1]
+        raise DNN_ShapeError.new("The shape of y does not match the input shape. y shape is #{y.shape[1..-1]}, but output shape is #{@layers.last.shape}.")
+      end
+    end
+
     def layers_shape_check
       @layers.each.with_index do |layer, i|
+        prev_shape = layer.prev_layer.shape
         if layer.is_a?(Layers::Dense)
-          prev_shape = layer.prev_layer.shape
           if prev_shape.length != 1
             raise DNN_ShapeError.new("layer index(#{i}) Dense:  The shape of the previous layer is #{prev_shape}. The shape of the previous layer must be 1 dimensional.")
           end
         elsif layer.is_a?(Layers::Conv2D) || layer.is_a?(Layers::MaxPool2D)
-          prev_shape = layer.prev_layer.shape
           if prev_shape.length != 3
             raise DNN_ShapeError.new("layer index(#{i}) Conv2D:  The shape of the previous layer is #{prev_shape}. The shape of the previous layer must be 3 dimensional.")
+          end
+        elsif layer.is_a?(Layers::RNN)
+          if prev_shape.length != 2
+            layer_name = layer.class.name.match("\:\:(.+)$")[1]
+            raise DNN_ShapeError.new("layer index(#{i}) #{layer_name}:  The shape of the previous layer is #{prev_shape}. The shape of the previous layer must be 3 dimensional.")
           end
         end
       end
     end
   end